data entry operator

business analyst

civil engineer

data analyst

data analyst/data architect Jobs in Lahore

data analyst/data architect

data engineer

Techbridge Consultancy Services

We are looking for a motivated Data Engineer with 3+ years of experience to join our growing data team. You will be responsible for building, optimizing, and maintaining data pipelines and solutions that support business intelligence, analytics, and automation. This is an onsite role in our Lahore office.Key Responsibilities<ul><li>Develop, maintain, and optimize ETL/ELT pipelines using Python and related libraries (Pandas, NumPy, PySpark).</li><li>Write and optimize complex SQL queries for PostgreSQL, SQL Server, and other RDBMS.</li><li>Work with AWS Cloud services (S3, Lambda, Glue, Athena, Step Functions, EventBridge) to design and manage scalable data workflows.</li><li>Handle data ingestion, transformation, and validation for reporting and analytics.</li><li>Automate manual processes and integrate data flows across different systems.</li><li>Collaborate with analysts and business teams to ensure reliable and timely delivery of datasets and reports.</li><li>Use Excel and other BI tools for quick data analysis and validation.</li><li>Ensure data quality, security, and compliance in all data operations.</li></ul>Required Skills<ul><li>3+ years of professional experience in data engineering, ETL, or backend development.</li><li>Strong proficiency in Python (Pandas, NumPy, PySpark).</li><li>Solid knowledge of SQL (PostgreSQL, SQL Server, or similar).</li><li>Experience with AWS Cloud services (S3, Lambda, Glue, Athena, Step Functions, EventBridge).</li><li>Hands-on experience in Excel for data validation and reporting.</li><li>Familiarity with data warehousing concepts and big data tools.</li><li>Understanding of data modeling, schema design, and performance optimization.</li><li>Strong problem-solving, analytical, and communication skills.</li></ul>Preferred<ul><li>Experience with job orchestration tools (Airflow, Step Functions, etc.).</li><li>Exposure to BI/Reporting tools (e.g., Power BI, QuickSight, Tableau).</li><li>Knowledge of APIs, REST, and data integration techniques.</li><li>Experience with Git and version control.</li></ul>What We Offer<ul><li>Opportunity to work with modern data engineering tools and AWS Cloud.</li><li>Professional growth in a collaborative and supportive environment.</li><li>Onsite role at a prime location in Gulberg III, Lahore</li></ul>Job Type: Full-timeApplication Question(s):<ul><li>How many years of professional experience do you have working with Python for data engineering or ETL pipelines?</li><li>How would you rate your proficiency in writing and optimizing SQL queries?</li><li>Are you comfortable working full-time onsite from 2:00 PM to 11:00 PM (PKT) in Gulberg III, Lahore?</li></ul>Work Location: In person

Data Engineer

ibex

<div>
 We are seeking a highly motivated and responsible
 
 Data Engineer
 
 to join our dynamic team. This role requires hands-on experience in building scalable data pipelines, managing structured and unstructured databases, and supporting end-to-end data operations. The ideal candidate will bring strong problem-solving skills, a collaborative mindset, and a commitment to data excellence.
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design, develop, and manage reliable and scalable data pipelines.
 </li>
 <li>
 Clean, validate, and transform data from multiple sources for analytics and operational use.
 </li>
 <li>
 Work with large datasets and ensure high data quality and availability.
 </li>
 <li>
 Develop and maintain ETL workflows using standard tools and scripting.
 </li>
 <li>
 Automate data extraction, transformation, and loading processes across systems.
 </li>
 <li>
 Monitor and optimize performance of data workflows for speed and efficiency.
 </li>
 <li>
 Develop, maintain, and optimize complex SQL queries, stored procedures, functions, and views.
 </li>
 <li>
 Design and implement relational database schemas and indexing strategies.
 </li>
 <li>
 Ensure data integrity, security, and compliance within SQL Server environments.
 </li>
 <li>
 Work with MongoDB for storing and querying unstructured or semi-structured data.
 </li>
 <li>
 Design document-based data models and manage performance tuning for MongoDB.
 </li>
 <li>
 Handle replication and backup strategies where applicable.
 </li>
 <li>
 Analyze complex data requirements and translate them into efficient technical solutions.
 </li>
 <li>
 Identify data-related issues, perform root-cause analysis, and deliver timely resolutions.
 </li>
 <li>
 Work closely with data analysts, software engineers, and business stakeholders to understand requirements.
 </li>
 <li>
 Participate in code reviews, team planning sessions, and cross-functional meetings.
 </li>
 <li>
 Take ownership of assigned tasks with accountability and attention to detail.
 </li>
 <li>
 Exhibit a proactive approach to delivering solutions and supporting team goals.
 </li>
 <li>
 Contribute to architectural discussions and recommend improvements based on industry best practices.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Information Systems, or a related field.
 </li>
 <li>
 2&ndash;3 years of experience in data engineering or database development roles.
 </li>
 <li>
 Strong proficiency in SQL Server (T-SQL, indexing, optimization).
 </li>
 <li>
 Hands-on experience with MongoDB or other NoSQL technologies.
 </li>
 <li>
 Familiarity with data pipeline tools and ETL development.
 </li>
 <li>
 Working knowledge of Python or similar scripting languages.
 </li>
 <li>
 Understanding of data modeling, normalization, and data warehousing concepts.
 </li>
 <li>
 Strong analytical thinking and problem-solving skills.
 </li>
 <li>
 Excellent communication and teamwork abilities.
 </li>
 </ul>
</div>

Data Engineer, Tech

NorthBay Solutions

<div>
 &nbsp;
 
 
 
 
 
 
 
 Job Title:
 
 
 
 
 
 
 
 
 
 
 
 
 Data Engineer (Snowflake)
 
 
 
 
 
 
 
 
 
 
 
 
 
 Location:
 
 
 
 
 
 
 
 
 
 
 
 
 Hybrid - Lahore, Karachi, Islamabad
 
 
 
 
 
 
 
 
 
 
 
 
 
 Experience:
 
 
 
 
 
 
 
 
 
 
 
 
 6-8 years (Minimum 4-6 years of Snowflake experience)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Job Category:
 
 
 
 
 
 
 
 
 
 
 
 
 Data Engineering
 
 
 
 
 
 
 
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Database Design &amp; Development:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Utilize Snowflake to design, develop, and optimize data architecture.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Work with PostgreSQL and other databases to manage and manipulate data.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Lead conversion projects from SQL-based platforms to Snowflake.
 
 
 
 
 
 
 </li>
 </ul>
 </li>
 <li>
 
 
 
 
 
 
 Programming &amp; Scripting:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Develop robust applications and scripts using C#, Java, and Python, or other relevant technologies.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Write efficient Snowflake functions and stored procedures using JavaScript.
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Implement big data solutions using Spark and PySpark (Plus).
 
 
 
 
 
 
 </li>
 </ul>
 </li>
 <li>
 
 
 
 
 
 
 Cloud Integration:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Implement data storage solutions using Amazon S3 (AWS).
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Integrate and manage data pipelines using AWS Glue (Plus).
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Utilize AWS Lambda for serverless computing (Plus).
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Contribute to cloud data strategies involving GCP (Plus).
 
 
 
 
 
 
 </li>
 </ul>
 </li>
 <li>
 
 
 
 
 
 
 Additional Database Management:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Work with Aurora and MSSQL for various data management tasks (Plus).
 
 
 
 
 
 
 </li>
 </ul>
 </li>
 </ul>
 
 
 
 
 
 
 Required Skills:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Languages:
 
 
 
 
 
 
 
 
 
 
 
 
 C#, Java, Python, or other relevant technologies
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Database:
 
 
 
 
 
 
 
 
 
 
 
 
 Snowflake (Design, Develop), PostgreSQL
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Cloud Tools:
 
 
 
 
 
 
 
 
 
 
 
 
 Amazon S3 (AWS)
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Scripting:
 
 
 
 
 
 
 
 
 
 
 
 
 JavaScript (for Snowflake functions and stored procedures)
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 Preferred Skills:
 
 
 
 
 
 
 <ul>
 <li>
 
 
 
 
 
 
 Big Data Technologies:
 
 
 
 
 
 
 
 
 
 
 
 
 Spark, PySpark
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Cloud Tools:
 
 
 
 
 
 
 
 
 
 
 
 
 AWS Glue, AWS Lambda, GCP
 
 
 
 
 
 
 </li>
 <li>
 
 
 
 
 
 
 Database:
 
 
 
 
 
 
 
 
 
 
 
 
 Aurora, MSSQL
 
 
 
 
 
 
 </li>
 </ul>
 
 
 
 
 
 
 Conversion:
 
 
 
 
 
 
 
 
 
 
 
 
 SQL to Snowflake code conversion
 
 
 
 
 
 
</div>

Data Engineer(Snow Flake)

Brand786 LTD

We are looking for a Data Analyst / Analytics Engineer to design and manage a modern data infrastructure that centralizes business data and delivers actionable insights across sales, marketing, and operations.Key Responsibilities<ul><li>Design and manage cloud-based data architecture</li><li>Build and maintain ETL/ELT data pipelines</li><li>Integrate data from CRM, marketing, website analytics, and operational systems</li><li>Develop interactive dashboards and reporting systems</li><li>Deliver weekly, monthly, and quarterly business reports</li><li>Analyze data to identify trends, insights, and performance improvements</li><li>Implement data governance, quality checks, and security standards</li><li>Collaborate with department heads to translate business needs into data insights</li></ul>Required Skills<ul><li>Advanced SQL</li><li>Experience with Python or R</li><li>Strong knowledge of data pipelines and ETL processes</li><li>Experience with BI tools (Power BI, Tableau, Looker, etc.)</li><li>Strong understanding of data modelling and analytics</li></ul>Preferred Skills<ul><li>Experience with Google Cloud or Microsoft Azure</li><li>Experience building data infrastructure from scratch</li><li>Knowledge of sales, marketing, and operational analytics</li></ul>Job Type: Full-timeLanguage:<ul><li>English (Required)</li></ul>Work Location: In person

Data Analyst

CodeNinja

<div>About CodeNinja
CodeNinja is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
Role Purpose
Lead the ERP program&rsquo;s data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
Key Responsibilities<ul><li>Conduct comprehensive assessment of legacy data sources:</li></ul>
o Inventory, Maintenance (MRO), Procurement, HR, Technical Docs<ul><li>Identify:</li></ul>
o Data quality issues (duplicates, missing, inconsistencies)
o Data ownership and governance gaps
o Redundant/siloed datasets<ul><li>Define data cleansing and standardization approach</li><li>Produce Data Readiness Assessment Report</li><li>Define end-to-end Data Migration Strategy, including:</li></ul>
o Migration approach (phased, module-wise, or big-bang)
o Data prioritization (master data vs transactional vs historical)<ul><li>Develop Data Mapping Specifications:</li></ul>
o Legacy ERP field-level mappings
o Transformation rules and standardization logic
o Handling of missing/invalid data<ul><li>Define Data Cleansing &amp; Preparation Plan:</li></ul>
o Deduplication rules
o Data enrichment where required
o Validation checkpoints before migration<ul><li>Design Migration Execution Plan:</li></ul>
o Migration cycles (mock runs, dry runs, final cutover)
o Rollback strategy in case of failure
o Downtime and cutover planning<ul><li>Define Data Validation &amp; Reconciliation Framework:</li></ul>
o Pre-migration vs post-migration validation rules
o Reconciliation reports (counts, totals, relationships)
o Sign-off criteria for each module<ul><li>Produce key deliverables:</li></ul>
o Data Migration Plan
o Data Mapping Documents
o Data Validation &amp; Reconciliation Reports<ul><li>Identify and enable AI/ML use cases, such as:</li></ul>
o Predictive maintenance modeling
o Inventory demand forecasting
o Supplier performance analytics<ul><li>Leverage AI tools for:</li></ul>
o Data profiling and anomaly detection
o Data quality assessment and cleansing recommendations
o Advanced analytics and insights generation<ul><li>Define enterprise conceptual data model:</li></ul>
o Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs<ul><li>Establish:</li></ul>
o Entity relationships
o Master data definitions
o Data standardization rules<ul><li>Support BI teams for dashboards and analytics</li><li>Align data models with business workflows</li><li>Ensure requirements are data-feasible and consistent</li></ul> 
Requirements 
3. Required Skills &amp; Experience
Mandatory<ul><li> 5 - 8 years in Data Analyst / Data Architecture roles</li><li>Experience in large-scale ERP or enterprise data transformation programs</li><li>Strong expertise in:</li></ul>
o Data modelling (conceptual &amp; logical)
o Data migration and cleansing
o Data warehousing and reporting
Technical Expertise<ul><li>Strong knowledge of:</li></ul>
o ETL processes and migration tools
o SQL and relational databases
o API-based integrations<ul><li>Experience with BI tools (Power BI, Tableau)</li></ul>
Preferred<ul><li>Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)</li><li>Exposure to:</li></ul>
o Maintenance (MRO) data
o Inventory systems
o Technical documentation repositories<ul><li>Demonstrated experience using AI/ML tools or platforms, such as:</li></ul>
o Data analysis and prediction tools
o AI-assisted data modeling or profiling tools<ul><li>Ability to translate data into AI-driven insights for decision-making</li></ul>
Why Join CodeNinja?<ul><li>
Work on impactful ERP transformation projects at enterprise scale
</li><li>Shape end-to-end data strategy, migration, and architecture
</li><li>Leverage AI/ML for advanced data insights and analytics
</li><li>Collaborate with cross-functional teams and drive business decisions
</li><li>Build scalable data models and governance frameworks
</li><li>Grow in a culture of innovation, ownership, and continuous learning</li></ul>
Equal Opportunity Statement
We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply. 
Benefits 
<ul><li>
Provident Fund</li><li>
Gym Membership
</li><li>Leaves as per the company policy
</li><li>Company-paid trips
</li><li>Easy Loan Facility for Employees
</li><li>Yearly increment
</li><li>Maternity Benefits (Leaves &amp; WFH)
</li><li>Health Insurance (Maternity covered) &ndash; includes spouse and parents (till age 80)</li></ul></div>

Data Analyst/Data Architect

CodeNinja Inc.

<div>
 
 About CodeNinja
 
 
 
 
 CodeNinja
 
 is a full-stack AI delivery company that helps enterprises, governments, and software acquirers build and operate intelligence-driven systems for mission-critical workflows. We specialize in deploying AI into real operations&mdash;combining strong engineering fundamentals with AI-native delivery to create measurable value, resilience, and long-term ownership for our clients. Our global footprint and delivery model are supported by AI Labs, AI Pods, and Global Capability Centers, enabling teams to co-engineer scalable platforms across regions and time zones.
 
 
 
 
 Role Purpose
 
 
 
 
 Lead the ERP program's data strategy by ensuring data readiness, conceptual data modelling, reporting data sourcing, and structured data migration planning, enabling a reliable, unified data foundation across all modules.
 
 
 
 Key Responsibilities
 
 
 
 <ul>
 <li>
 Conduct comprehensive assessment of legacy data sources:
 </li>
 <li>
 Inventory, Maintenance (MRO), Procurement, HR, Technical Docs
 </li>
 <li>
 Identify:
 </li>
 <li>
 Data quality issues (duplicates, missing, inconsistencies)
 </li>
 <li>
 Data ownership and governance gaps
 </li>
 <li>
 Redundant/siloed datasets
 </li>
 <li>
 Define data cleansing and standardization approach
 </li>
 <li>
 Produce Data Readiness Assessment Report
 </li>
 <li>
 Define end-to-end Data Migration Strategy, including:
 </li>
 <li>
 Migration approach (phased, module-wise, or big-bang)
 </li>
 <li>
 Data prioritization (master data vs transactional vs historical)
 </li>
 <li>
 Develop Data Mapping Specifications:
 </li>
 <li>
 Legacy &rarr; ERP field-level mappings
 </li>
 <li>
 Transformation rules and standardization logic
 </li>
 <li>
 Handling of missing/invalid data
 </li>
 <li>
 Define Data Cleansing &amp; Preparation Plan:
 </li>
 <li>
 Deduplication rules
 </li>
 <li>
 Data enrichment where required
 </li>
 <li>
 Validation checkpoints before migration
 </li>
 <li>
 Design Migration Execution Plan:
 </li>
 <li>
 Migration cycles (mock runs, dry runs, final cutover)
 </li>
 <li>
 Rollback strategy in case of failure
 </li>
 <li>
 Downtime and cutover planning
 </li>
 <li>
 Define Data Validation &amp; Reconciliation Framework:
 </li>
 <li>
 Pre-migration vs post-migration validation rules
 </li>
 <li>
 Reconciliation reports (counts, totals, relationships)
 </li>
 <li>
 Sign-off criteria for each module
 </li>
 <li>
 Produce key deliverables:
 </li>
 <li>
 Data Migration Plan
 </li>
 <li>
 Data Mapping Documents
 </li>
 <li>
 Data Validation &amp; Reconciliation Reports
 </li>
 <li>
 Identify and enable AI/ML use cases, such as:
 </li>
 <li>
 Predictive maintenance modeling
 </li>
 <li>
 Inventory demand forecasting
 </li>
 <li>
 Supplier performance analytics
 </li>
 <li>
 Leverage AI tools for:
 </li>
 <li>
 Data profiling and anomaly detection
 </li>
 <li>
 Data quality assessment and cleansing recommendations
 </li>
 <li>
 Advanced analytics and insights generation
 </li>
 <li>
 Define enterprise conceptual data model:
 </li>
 <li>
 Assets, Inventory, Work Orders, Suppliers, Workforce, Technical Docs
 </li>
 <li>
 Establish:
 </li>
 <li>
 Entity relationships
 </li>
 <li>
 Master data definitions
 </li>
 <li>
 Data standardization rules
 </li>
 <li>
 Support BI teams for dashboards and analytics
 </li>
 <li>
 Align data models with business workflows
 </li>
 <li>
 Ensure requirements are data-feasible and consistent
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Required Skills &amp; Experience
 
 
 </li>
 </ul>
 
 Mandatory
 
 
 
 <ul>
 <li>
 5 - 8 years in Data Analyst / Data Architecture roles
 </li>
 <li>
 Experience in large-scale ERP or enterprise data transformation programs
 </li>
 <li>
 Strong expertise in:
 </li>
 <li>
 Data modelling (conceptual &amp; logical)
 </li>
 <li>
 Data migration and cleansing
 </li>
 <li>
 Data warehousing and reporting
 
 
 </li>
 </ul>
 
 Technical Expertise
 
 
 
 <ul>
 <li>
 Strong knowledge of:
 </li>
 <li>
 ETL processes and migration tools
 </li>
 <li>
 SQL and relational databases
 </li>
 <li>
 API-based integrations
 </li>
 <li>
 Experience with BI tools (Power BI, Tableau)
 
 
 </li>
 </ul>
 
 Preferred
 
 
 
 <ul>
 <li>
 Experience in ERP &amp; Enterprise Data Management (logistics, manufacturing)
 </li>
 <li>
 Exposure to:
 </li>
 <li>
 Maintenance (MRO) data
 </li>
 <li>
 Inventory systems
 </li>
 <li>
 Technical documentation repositories
 </li>
 <li>
 Demonstrated experience using AI/ML tools or platforms, such as:
 </li>
 <li>
 Data analysis and prediction tools
 </li>
 <li>
 AI-assisted data modeling or profiling tools
 </li>
 <li>
 Ability to translate data into AI-driven insights for decision-making
 
 
 </li>
 </ul>
 
 Why Join CodeNinja?
 
 
 
 <ul>
 <li>
 Work on impactful ERP transformation projects at enterprise scale
 </li>
 <li>
 Shape end-to-end data strategy, migration, and architecture
 </li>
 <li>
 Leverage AI/ML for advanced data insights and analytics
 </li>
 <li>
 Collaborate with cross-functional teams and drive business decisions
 </li>
 <li>
 Build scalable data models and governance frameworks
 </li>
 <li>
 Grow in a culture of innovation, ownership, and continuous learning
 
 
 </li>
 </ul>
 
 Equal Opportunity Statement
 
 
 
 We are an equal opportunity employer and are committed to fostering an inclusive, diverse, and equitable workplace. We do not discriminate based on race, religion, gender, age, disability, nationality, marital status, or any other protected characteristic under applicable law. We encourage candidates from all backgrounds to apply.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 Provident Fund
 </li>
 <li>
 Gym Membership
 </li>
 <li>
 Leaves as per the company policy
 </li>
 <li>
 Company-paid trips
 </li>
 <li>
 Easy Loan Facility for Employees
 </li>
 <li>
 Yearly increment
 </li>
 <li>
 Maternity Benefits (Leaves &amp; WFH)
 </li>
 <li>
 Health Insurance (Maternity covered) - includes spouse and parents (till age 80)
 </li>
 </ul>
</div>

Stewart Pakistan Private Limited

<div>
 
 DATABRICKS ARCHITECT
 
 
 Job Description&middot; Engineering Leadership
 
 
 Department Data Engineering / Platform
 
 
 Experience 5+ Years (Databricks / Lakehouse)
 
 
 
 
 
 
 Role Overview
 
 
 
 We are looking for a hands-on, senior Databricks Architect to design, build, and govern our Lakehouse data platform from the ground up. You will own the end-to-end architecture of our data infrastructure &mdash; from raw ingestion through the Medallion layers to serving &mdash; and establish the engineering standards that will guide the entire data organization.
 
 
 This is a highly strategic and technical role focused on driving adoption of Databricks, Unity Catalog, and modern Lakehouse patterns across all data products and pipelines.
 
 
 
 
 
 
 Key Responsibilities
 
 
 
 
 Lakehouse Architecture &amp; Design
 
 
 <ul>
 <li>
 Design and implement a production-grade Medallion Architecture (Bronze / Silver / Gold) across all data pipelines.
 </li>
 <li>
 Establish best practices for Delta Lake table design, partitioning strategies, Z-ordering, and optimization across large-scale datasets.
 </li>
 <li>
 Define data modeling standards and schema evolution policies across the Lakehouse.
 </li>
 <li>
 Architect end-to-end data flows from ingestion (streaming and batch) through transformation and serving layers.
 </li>
 </ul>
 
 
 
 
 
 Unity Catalog &amp; Data Governance
 
 
 <ul>
 <li>
 Lead the setup, configuration, and rollout of Unity Catalog as the centralized governance layer for all data assets.
 </li>
 <li>
 Design meta store hierarchy, catalog/schema/table organization, and tagging standards.
 </li>
 <li>
 Implement fine-grained access control (row-level, column-level), data masking policies, and audit logging.
 </li>
 <li>
 Establish data lineage tracking and ensure end-to-end visibility across all pipelines.
 </li>
 <li>
 Define and enforce data classification and sensitivity frameworks for PII and regulated data assets.
 </li>
 </ul>
 
 
 
 
 
 Pipeline Development &amp; Orchestration
 
 
 <ul>
 <li>
 Build and maintain production-grade data pipelines using PySpark, Delta Live Tables (DLT), and Databricks Workflows / Jobs.
 </li>
 <li>
 Design modular, reusable pipeline patterns including incremental ingestion, CDC (Change Data Capture), and full-refresh strategies.
 </li>
 <li>
 Implement robust pipeline observability: logging, alerting, lineage tracking, and SLA monitoring.
 </li>
 <li>
 Leverage Databricks Repos for CI/CD integration, managing code promotion across dev / staging / production environments.
 </li>
 </ul>
 
 
 
 
 
 Performance &amp; Compute Optimization
 
 
 <ul>
 <li>
 Optimize Spark execution plans, identify and resolve performance bottlenecks across large-scale distributed workloads.
 </li>
 <li>
 Right-size cluster configurations: Serverless warehouses, auto-scaling job clusters, and photon-enabled SQL warehouses.
 </li>
 <li>
 Leverage Serverless Warehouses and SQL Warehouses for BI and ad hoc analytics workloads, minimizing cost and cold-start latency.
 </li>
 <li>
 Manage cost governance for compute, storage, and DBU consumption across workspaces.
 </li>
 </ul>
 
 
 
 
 
 Developer Experience &amp; Standards
 
 
 <ul>
 <li>
 Set up and maintain Databricks Repos with standardized project structures and Git integration.
 </li>
 <li>
 Define Python coding standards, notebook best practices, and modular library patterns for the data engineering team.
 </li>
 <li>
 Build reusable Python utility libraries for common patterns: schema validation, data quality checks, Delta operations, and logging.
 </li>
 <li>
 Establish unit testing and integration testing frameworks for Spark pipelines.
 </li>
 </ul>
 
 
 
 
 
 Security, Compliance &amp; Networking
 
 
 <ul>
 <li>
 Configure workspace-level and account-level security: Private Link, IP access lists, secrets management via Databricks Secrets or AWS Secrets Manager.
 </li>
 <li>
 Design and enforce network isolation for sensitive data workloads.
 </li>
 <li>
 Ensure compliance with data residency and access control requirements for customer data.
 </li>
 </ul>
 
 
 
 
 
 Collaboration &amp; Enablement
 
 
 <ul>
 <li>
 Partner with data engineers, data scientists, and analytics engineers to ensure the platform meets diverse workload needs.
 </li>
 <li>
 Mentor the engineering team on Databricks, Spark optimization, and Lakehouse best practices.
 </li>
 <li>
 Produce architectural documentation, runbooks, and internal knowledge bases.
 </li>
 <li>
 Evaluate and recommend new Databricks features and third-party integrations relevant to the organization's data roadmap.
 </li>
 </ul>
 
 
 
 
 
 Required Qualifications
 
 
 
 
 Core Databricks &amp; Lakehouse
 
 
 <ul>
 <li>
 5+ years of hands-on experience with Databricks, with at least 2 years in an architect or senior lead role.
 </li>
 <li>
 Deep expertise in Unity Catalog: metastore setup, three-level namespace, ACL design, and data governance workflows.
 </li>
 <li>
 Strong mastery of the Medallion Architecture and Delta Lake: ACID transactions, time travel, compaction, and OPTIMIZE/VACUUM strategies.
 </li>
 <li>
 Proven experience designing and deploying production pipelines with Databricks Jobs and Workflows, including multi-task job DAGs, retry logic, and notifications.
 </li>
 <li>
 Hands-on experience with Databricks Repos and CI/CD integration for notebook and Python library deployments.
 </li>
 <li>
 Experience configuring and operating Serverless SQL Warehouses and Serverless compute for Jobs.
 </li>
 </ul>
 
 
 
 
 
 Apache Spark
 
 
 <ul>
 <li>
 Expert-level PySpark development: DataFrames, Spark SQL, window functions, broadcast joins, and UDFs.
 </li>
 <li>
 Strong understanding of Spark internals: DAG execution, shuffle optimization, memory management, and speculative execution.
 </li>
 <li>
 Experience with structured streaming and micro-batch processing patterns.
 </li>
 <li>
 Proven ability to diagnose and resolve Spark performance issues using Spark UI and event logs.
 </li>
 </ul>
 
 
 
 
 
 Python &amp; Software Engineering
 
 
 <ul>
 <li>
 Advanced Python skills with a strong software engineering background: packaging, testing (pytest), virtual environments, and dependency management.
 </li>
 <li>
 Experience building modular Python libraries for data engineering use cases.
 </li>
 <li>
 Familiarity with common data engineering libraries: pandas, pydantic, great_expectations or similar DQ frameworks.
 </li>
 </ul>
 
 
 
 
 
 Cloud &amp; Infrastructure
 
 
 <ul>
 <li>
 Experience deploying Databricks on AWS, including workspace provisioning, IAM integration, and VPC configuration.
 </li>
 <li>
 Familiarity with cloud-native storage (S3/ADLS), external locations in Unity Catalog, and storage credentials management.
 </li>
 <li>
 Exposure to infrastructure-as-code tooling (Terraform, Databricks Asset Bundles, or similar).
 </li>
 </ul>
 
 
 
 
 
 Preferred Qualifications
 
 
 <ul>
 <li>
 Databricks Certified Data Engineer Professional or Databricks Certified Associate Developer for Apache Spark certifications.
 </li>
 <li>
 Experience with Delta Live Tables (DLT) for declarative pipeline authoring.
 </li>
 <li>
 Familiarity with dbt (data build tool) integrated with Databricks SQL.
 </li>
 <li>
 Experience with Databricks Feature Store or MLflow for ML platform use cases.
 </li>
 <li>
 Exposure to Databricks Marketplace and Partner Connect integrations.
 </li>
 <li>
 Experience with Elasticsearch, Apache Kafka, or other streaming/search technologies complementary to the Lakehouse.
 </li>
 </ul>
 
 
 
 
 
 Core Technology Stack
 
 
 
 
 
 <ul>
 <li>
 Databricks
 </li>
 <li>
 Apache Spark Delta Lake
 </li>
 <li>
 Unity Catalog
 </li>
 <li>
 Medallion Architecture
 </li>
 <li>
 Databricks Jobs
 </li>
 <li>
 Databricks Repos
 </li>
 <li>
 DLT
 </li>
 <li>
 Python / PySpark
 </li>
 <li>
 Serverless Warehouses
 </li>
 <li>
 AWS / S3
 </li>
 <li>
 CI/CD
 </li>
 </ul>
</div>

Senior Data Bricks Architect

Explore 429+ Data engineer in Lahore this April. Find roles across top companies and apply now to boost your career.

429 data engineer jobs In Lahore

Data Engineer

Data Engineer, Tech

Data Engineer(Snow Flake)

Data Analyst

Data Analyst/Data Architect

Data Analyst/Data Architect

Senior Data Bricks Architect